Schedule

Calendar of resources

The material in this module is designed to be experienced in an intensive one week format followed by an assessment meant to showcase reproducible statistical analysis skills. For enrolled students, the work will be supported with several live sessions during the main week of delivery.

Preparation: If you have no Python programming experience or would like to strengthen your skills, you may find it useful to practice before the module week.

Day	Topics	Labs
Mon am vid1 vid2 pm vid1	01 Introduction 1.1 02 Linear algebra 2.1 03 Probability 3.1	00 Lab Preparation 01 Anaconda and Python labs 01 Python labs 1:7 02 Pandas labs 1:6
Tues am vid1 pm (no vid)	04 Numerical computation 4.1 4.2 05 Machine learning 5.1 06 Deep networks 6.1 6.2	Chollet 2021 Ch 03 02 Colab deep learning labs 03 Deep learning labs 1:6 04 Computer viz labs 1:6
Wed am (no meeting) pm (no meeting)	07 Regularization 7.1 08 Stochastic gradient descent 8.1 8.2	Finish previous or work through Chollet 2021 Ch 04, Ch 05, Ch06, Ch 07, Ch 08, Ch 09 Ch 04 notebook Ch 05 notebook Ch 07 notebook Ch 08 notebook Ch 9.1, 9.2, 9.3
Thurs am pm	09 Convolutional networks 9.1 9.2 10 Recurrent networks 10.1	Tensorflow example + your own experiments weevil watch repo
Fri am pm	11 Practical methods 11.1 12 Applications 12.1 12.2	Yolo example + your own experiments

Mon

vid1